Context-Aware Form Input Suggestions via Semantic Tag Analysis
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Solution Overview
Problem
Existing form autocompletion systems fail to consider the context of user actions when providing input suggestions, often suggesting irrelevant values and not offering relevant dates or information, leading to increased user effort and potential errors in form filling.
Innovation Solution
A system that uses semantic tags in web resources to determine the intent and parameters of form fields, allowing for context-aware suggestions by analyzing itemprop attributes within form and input tags, and providing personalized suggestions based on user data while ensuring user control over data collection and usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional form autocompletion is used that only considers field names, then implementation is simple, but suggestion relevance is poor and user effort increases
Solution Approach 1:
The system performs preliminary actions by collecting and storing user data from various sources (emails, calendars, documents) before form completion is needed. This pre-collected data is then readily available for context-aware suggestions, eliminating the need for users to manually search or type information that is already stored in their digital ecosystem.
Solution Approach 2:
The patent introduces an intermediary component (the suggestion system) that sits between the user and the form fields. This intermediary analyzes the form context, retrieves relevant user data from multiple sources, and presents filtered suggestions, thereby improving relevance without requiring the user to directly access or manage the underlying data sources.
2Measurement precision
If context-aware suggestions are implemented using semantic tags, then suggestion accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by collecting and storing user data from various sources (emails, calendars, documents) before form completion is needed. This pre-collected data is then readily available for context-aware suggestions, eliminating the need for users to manually search or type information that is already stored in their digital ecosystem.
Solution Approach 2:
The system changes parameters by analyzing semantic tags and form context to dynamically adjust what data is retrieved and how suggestions are generated. Instead of processing all user data uniformly, the system modifies its processing parameters based on the specific form context, thereby reducing unnecessary computational overhead while maintaining accuracy.
3Ease of operation
If more user data is collected for personalized suggestions, then suggestion quality improves, but user privacy concerns increase
Solution Approach 1:
The system applies local quality by selectively accessing and using only the specific user data that is relevant to the current form context. Instead of collecting or processing all user data uniformly, the system retrieves only the necessary information (e.g., flight dates for a car rental form), thereby minimizing privacy exposure while maintaining suggestion quality.
Solution Approach 2:
The system implements feedback mechanisms where user interactions with suggestions are tracked and used to improve future suggestion quality. This allows the system to learn from user preferences and behaviors, progressively improving ease of operation without needing to collect additional sensitive data, as the learning is based on observed patterns rather than raw data collection.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for facilitating input by a user into a form. In one aspect, a method include actions of obtaining a web resource that includes a form, determining a particular field of the form has been selected, determining an intent that corresponds to the form from a first semantic tag in the web resource, determining a parameter of the intent that corresponds to the particular field of the form from a second semantic tag in the web resource, determining a value to suggest for the particular field based at least on the intent and the parameter of the intent, and providing the value for output as a suggestion of input for the particular field.